Power BI Quality and Productivity Dashboard Training Course

Course overview

Operations and project teams often track quality defects, rework, throughput, labour hours, schedule adherence and corrective actions in separate spreadsheets or disconnected systems. Managers receive static reports too late to identify emerging bottlenecks, while analysts spend excessive time reconciling data instead of explaining what is driving performance. This course addresses the practical challenge of turning operational data into a governed Power BI dashboard that shows where quality losses and productivity constraints are occurring, who owns the action, and whether improvement efforts are working.

Participants build quality and productivity reporting models in Power BI using realistic production, service delivery and project operations data. They learn to define useful KPIs; clean and combine source files with Power Query; create a star-schema data model; write DAX measures for defect rate, first-pass yield, rework cost, output per labour hour, plan-versus-actual performance and rolling trends; and design dashboards that support daily management and management review. The course also covers drill-through analysis, variance investigation, target setting, conditional alerts and row-level security for controlled distribution.

Training is delivered through instructor demonstrations, guided dashboard builds and scenario-based workshops. Each participant develops a working Quality and Productivity Performance Dashboard with an executive scorecard, operational detail pages, root-cause views and documented KPI definitions. They leave with reusable report-design patterns, DAX measure examples, a data-model blueprint and an implementation plan for applying the dashboard to their own operation.

The course is suited to professionals who already work with operational, project, manufacturing, service or quality data and need to produce decision-ready Power BI reporting rather than isolated charts.

Course objectives

By the end of this course, participants will be able to:

• Define a quality and productivity KPI framework covering defects, yield, rework, throughput, labour efficiency and plan-versus-actual performance
• Prepare operational source data using Power Query transformations, data types, error handling and refresh-ready query steps
• Build a star-schema Power BI data model with fact tables, dimensions, relationships and a dedicated calendar table
• Create DAX measures for defect rate, first-pass yield, rework cost, output per labour hour and rolling-period trends
• Design an executive quality and productivity scorecard with targets, variances, conditional formatting and exception indicators
• Develop drill-through and decomposition analysis pages that isolate performance by site, team, product, project or process step
• Apply row-level security and Power BI Service workspace practices for controlled dashboard sharing and governance
• Produce a documented Quality and Productivity Performance Dashboard and a deployment plan for a live business use case

Benefits of attending

Target competencies

Who should attend

• Operations Managers — who need timely visibility of throughput, capacity constraints, rework and team performance
• Quality Managers — who must monitor defect patterns, corrective actions, yield and quality-cost trends
• Project Controls Analysts — who compare planned output, actual progress, resource effort and delivery performance
• Continuous Improvement Specialists — who require evidence to prioritise Lean, Six Sigma or process-improvement interventions
• Business Intelligence Analysts — who build governed Power BI reports from operational and quality data sources
• Production or Service Delivery Supervisors — who need actionable daily-management views for teams, shifts and work areas

Requirements and prerequisites

Participants should be comfortable working with structured business data in Excel or a similar tabular tool, including columns, filters, basic formulas and data quality checks. They should understand the operational meaning of measures such as output, defects, rework, labour hours, targets and variances in their own environment. Prior use of Power BI is helpful but not essential; the course introduces Power Query, data modelling and DAX from an applied intermediate level. Participants do not need programming, SQL, statistical modelling or prior dashboard-design experience. A Windows laptop with permission to install or access Power BI Desktop is strongly recommended.

Training methodology

The course combines focused instructor-led explanations with daily Power BI build sessions using a realistic operational dataset containing production volumes, defects, labour hours, targets and corrective actions. Participants clean source data, model relationships, write DAX measures and progressively assemble dashboard pages rather than following isolated software demonstrations. Case discussions examine misleading KPIs, incomplete targets and root-cause questions from management meetings. Small-group design reviews test whether each dashboard answers a specific operational decision. On the final day, participants complete their dashboard and prepare a practical data, refresh and adoption plan.

Course outline

Day 1: Quality and productivity reporting foundations

• Operational performance questions and dashboard decision use cases
• Quality, productivity and cost-of-poor-quality KPI definitions
• Leading and lagging indicators for daily management
• Target, tolerance and escalation threshold design
• Power BI Desktop interface and report-building workflow
• Source-data assessment for operational reporting
• Dashboard wireframing for executive and frontline audiences

Workshop: Participants convert a business scenario into a KPI dictionary and a two-page dashboard wireframe for quality and productivity review.

Day 2: Preparing operational data with Power Query

• Importing Excel, CSV and folder-based operational data
• Power Query data profiling and column quality checks
• Data-type management for dates, quantities, durations and costs
• Cleaning defect codes, work-centre names and team identifiers
• Appending periodic production and quality files
• Merging lookup tables for products, sites, shifts and projects
• Query parameters and refresh-ready transformation design

Workshop: Participants build a repeatable Power Query pipeline that cleans and combines monthly production, labour and defect records.

Day 3: Data modelling and DAX performance measures

• Star-schema design for quality and productivity analytics
• Fact tables, dimension tables and relationship cardinality
• Creating and marking a dedicated date table
• DAX measure syntax and filter-context fundamentals
• Defect rate, first-pass yield and rework-cost measures
• Output-per-labour-hour and plan-versus-actual calculations
• Month-to-date, rolling-period and prior-period comparison measures

Workshop: Participants create a working semantic model and DAX measure set for yield, defects, productivity and performance variance.

Day 4: Dashboard design and root-cause analysis

• Executive scorecards and operational detail-page architecture
• Selecting visuals for targets, trends, rankings and exceptions
• Conditional formatting and status indicators for threshold breaches
• Slicers, synchronized filters and field parameters
• Drill-through pages for site, team, product and process analysis
• Decomposition trees and key influencers for diagnostic exploration
• Accessibility, visual hierarchy and report-performance practices

Workshop: Participants build interactive scorecard and root-cause pages that identify the segments contributing most to quality or productivity loss.

Day 5: Publishing, governance and implementation

• Power BI Service workspaces and publication workflow
• Dataset refresh planning and gateway considerations
• Row-level security roles for site and team access
• Dashboard distribution, subscriptions and management review routines
• KPI documentation and data-lineage records
• Testing dashboard accuracy against source reports
• Adoption planning and continuous dashboard improvement

Workshop: Participants publish or simulate publication of their completed dashboard, document KPI logic and produce a 90-day implementation plan.

Tools & standards covered

Microsoft Power BI Desktop, Microsoft Power BI Service, Power Query, DAX

A typical training day

Live online deliveries follow the same structure in the East Africa Time zone, with shorter screen blocks and longer breaks.

What the fee includes

How you can take this course

Certification

Participants who complete the full five days receive the Skillset Development Certificate of Completion, stating the course title, course code, dates and delivery format — suitable for professional-development records and employer reimbursement.

Frequently asked questions